Robots with Privacy Stipulations

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Abstract

In late July last year, it came to light that iRobot Corp. intended to sell the maps that modern
Roomba vacuum cleaning robots build to help them navigate. This caused a public furor among
consumers. This situation and several others (e.g., nuclear inspection, use of untrusted cloud
computing infrastructure) suggest that we might be interested in limiting what information a robot
might divulge. How should we think about robotic privacy? In this talk I’ll describe a line of research
that is concerned with this question, starting by showing that cryptography doesn’t solve the
problem. I’ll begin by examining a privacy-preserving tracking task, then look at how one might think
about estimators that are constrained to ensure they never know too much. Finally, I’ll talk about
planning subject to information disclosure constraints and introduce a useful structure that we call a
“plan closure.”